Digital Twin: Enabling Technologies, Challenges and Open Research

Digital Twin technology is an emerging concept that has become the centre of attention for industry and, in more recent years, academia. The advancements in industry 4.0 concepts have facilitated its growth, particularly in the manufacturing industry. The Digital Twin is defined extensively but is b...

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Veröffentlicht in:	IEEE access Jg. 8; S. 108952 - 108971
Hauptverfasser:	Fuller, Aidan, Fan, Zhong, Day, Charles, Barlow, Chris
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	applications Artificial intelligence Computational modeling Data analysis Data models deep learning Digital twins enabling technologies Industrial applications industrial Internet of Things (IIoT) Internet of Things Internet of Things (IoT) literature review machine learning Manufacturing Smart cities Virtual environments
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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Abstract	Digital Twin technology is an emerging concept that has become the centre of attention for industry and, in more recent years, academia. The advancements in industry 4.0 concepts have facilitated its growth, particularly in the manufacturing industry. The Digital Twin is defined extensively but is best described as the effortless integration of data between a physical and virtual machine in either direction. The challenges, applications, and enabling technologies for Artificial Intelligence, Internet of Things (IoT) and Digital Twins are presented. A review of publications relating to Digital Twins is performed, producing a categorical review of recent papers. The review has categorised them by research areas: manufacturing, healthcare and smart cities, discussing a range of papers that reflect these areas and the current state of research. The paper provides an assessment of the enabling technologies, challenges and open research for Digital Twins.
AbstractList	Digital Twin technology is an emerging concept that has become the centre of attention for industry and, in more recent years, academia. The advancements in industry 4.0 concepts have facilitated its growth, particularly in the manufacturing industry. The Digital Twin is defined extensively but is best described as the effortless integration of data between a physical and virtual machine in either direction. The challenges, applications, and enabling technologies for Artificial Intelligence, Internet of Things (IoT) and Digital Twins are presented. A review of publications relating to Digital Twins is performed, producing a categorical review of recent papers. The review has categorised them by research areas: manufacturing, healthcare and smart cities, discussing a range of papers that reflect these areas and the current state of research. The paper provides an assessment of the enabling technologies, challenges and open research for Digital Twins.
Author	Day, Charles Fuller, Aidan Barlow, Chris Fan, Zhong
Author_xml	– sequence: 1 givenname: Aidan orcidid: 0000-0002-3391-2407 surname: Fuller fullname: Fuller, Aidan email: a.fuller@keele.ac.uk organization: School of Computing and Mathematics, Keele University, Keele, U.K – sequence: 2 givenname: Zhong surname: Fan fullname: Fan, Zhong organization: School of Computing and Mathematics, Keele University, Keele, U.K – sequence: 3 givenname: Charles surname: Day fullname: Day, Charles organization: School of Computing and Mathematics, Keele University, Keele, U.K – sequence: 4 givenname: Chris surname: Barlow fullname: Barlow, Chris organization: Astec IT Solutions Ltd., Rugeley, U.K
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SubjectTerms	applications Artificial intelligence Computational modeling Data analysis Data models deep learning Digital twins enabling technologies Industrial applications industrial Internet of Things (IIoT) Internet of Things Internet of Things (IoT) literature review machine learning Manufacturing Smart cities Virtual environments
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Title	Digital Twin: Enabling Technologies, Challenges and Open Research
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